Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [30]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
import pandas as pd

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [13]:
df_2007 = df.query('year==2007')
df_2007_new = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_new, x="pop", orientation='h', color = df_2007_new.index, text_auto='.3s')
fig.show()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [33]:
fig = px.bar(df_2007_new, x="pop", orientation='h', color = df_2007_new.index)
fig.update_layout(yaxis={'categoryorder':'total ascending'})
fig.show()

Question 3:¶

Add text to each bar that represents the population

In [17]:
fig = px.bar(df_2007_new, x="pop", orientation='h', color = df_2007_new.index, text_auto='.3s')
fig.update_layout(yaxis={'categoryorder':'total ascending'})
fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [54]:
fig = px.bar(df, y="continent", x="pop", color="continent",
  animation_frame="year", animation_group="country", range_x=[0,4000000000])


fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [39]:
df['country'].unique().__len__() #amount of countries, 142 countries
len(df) #length of dataframe, 1704 rows 
1704/142 #amount of years of data per country, 12 years 

keys = [i for i in range(142)]
all_dataframes = {}
for i, country in zip(keys, df['country'].unique()):
    df2 = df[df['country'] == country].sort_values('year', ascending=True)
    all_dataframes[i] = df2
    
master_df = []
for i in all_dataframes:
    master_df.append(all_dataframes[i])
    
df_all = pd.concat(master_df)
df_all

fig = px.bar(df_all, x='pop', y="country", color='country',
  animation_frame="year", animation_group="country")
fig.update_layout(yaxis={'categoryorder':'total ascending'})
fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [40]:
df['country'].unique().__len__() #amount of countries, 142 countries
len(df) #length of dataframe, 1704 rows 
1704/142 #amount of years of data per country, 12 years 

keys = [i for i in range(142)]
all_dataframes = {}
for i, country in zip(keys, df['country'].unique()):
    df2 = df[df['country'] == country].sort_values('year', ascending=True)
    all_dataframes[i] = df2
    
master_df = []
for i in all_dataframes:
    master_df.append(all_dataframes[i])
    
df_all = pd.concat(master_df)
df_all

fig = px.bar(df_all, x='pop', y="country", color='country',
  animation_frame="year", animation_group="country", height=1000)
fig.update_layout(yaxis={'categoryorder':'total ascending'})
fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [43]:
fig.update_yaxes(range=(131.5, 142.5))
In [ ]: